I-Corps: Versatile Statistical Platform to Analyze, Diagnose, Track, and Treat Neurological Disorders

I-Corps：用于分析、诊断、跟踪和治疗神经系统疾病的多功能统计平台

• 批准号: 1443349
• 负责人: Elizabeth Torres
• 金额: $ 5万
• 依托单位: Rutgers University New Brunswick
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1443349&HistoricalAwards=false
• 关键词: Corps; Versatile; Statistical; Platform; Analyze

This proposal focuses on a new statistical platform paired with wearable sensing technology that objectively and automatically assesses real-time changes in the intentional and spontaneous aspects of physical motions embedded in natural human behaviors. The proposed activity will also help the team to better customize the behavioral motion data collection and analysis to address different needs of potential customers. Such customization can lead to more insight on various scientific questions involving the interconnections between brain and body functions during naturalistic behaviors, behavioral and pharmacological interventions, as well as in sports and performance training.The proposed activity (Statistical Platform for Individualized Behavioral Analyses, SPIBA) addresses two fundamental gaps in current analytical techniques for motion capture data: (1) The lack of real time capability within physiologically relevant time scales and frequencies; (2) The reliance on expected values from population averages rather than from the individual's inherent physiological features. SPIBA does not assume the Theoretical Gaussian distribution or homogeneous variance of motion parameters. Instead, the underlying probability distributions of various motion trajectory parameters along with their real time shifts in noise to signal ratios are estimated. These estimates and their rates of change are unique to the individual and therefore amenable to develop treatment effectiveness metrics for truly personalized medicine.

该提案的重点是一个新的统计平台，与可穿戴传感技术相结合，客观地自动评估自然人类行为中嵌入的物理运动的有意和自发方面的实时变化。拟议的活动还将帮助团队更好地定制行为运动数据收集和分析，以满足潜在客户的不同需求。这种定制可以导致对各种科学问题的更深入的了解，这些问题涉及自然行为、行为和药物干预以及体育和表演训练中大脑和身体功能之间的相互联系。（Statistical Platform for Individualized Behavioral Analyses，SPIBA）解决了当前运动捕捉数据分析技术中的两个基本差距：（1）在生理相关的时间尺度和频率内缺乏真实的时间能力;（2）依赖于来自群体平均值的预期值，而不是来自个体固有的生理特征。SPIBA不假设运动参数的理论高斯分布或均匀方差。相反，估计各种运动轨迹参数的潜在概率分布沿着其噪声信号比的真实的时移。这些估计值及其变化率对个体来说是独特的，因此可以为真正的个性化医疗制定治疗有效性指标。